Sentence examples for model order is from inspiring English sources

In order to improve the calculation efficiency, the modeling procedure that specifies the search path of the optimal model order is considered in this article.

Furthermore, we show that using this input allows J to be estimated consistently even when the model order is lower than the true system order.

This so-called optimal model order is selected from the convergence of a global order-wise signal-to-noise ratio index.

Model order is determined using Akaike information criterion and the model parameters are estimated through the application of partial least squares to attain a stable solution.

Subsequent to the question of the most adequate model structure, the choice of optimal model order is addressed, as in particular the optimal parametrization of the noise model is not obvious.

The results further demonstrated that a large model order is required to estimate all poles and residues of the original noisy signals, and that the row number corresponding to a weak mode of the isolated pole matrix could be easily determined via finite element analysis or engineering experiences.

Important issues concerning the generation of the data set and the estimation of the model order are discussed.

Parameters and model order are estimated using regularized least-squares inversion with lp norm penalty, where p≤1.

The BIC matrix calculations show that the best ARIMAX model order are equal to (1, 0, 2).

Through Akaike's criterion [McQuarrie and Tsai, 1998] the model order was selected as six.

Thus, our 5-TR model order was relatively conservative in the context of the hemodynamic filter.